基于遗传算法的图像分割技术

Chong Tan, Ying Sun, Gongfa Li, Bo Tao, Shuang Xu, Fei Zeng
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引用次数: 10

摘要

图像分割技术是数字图像研究领域的重要课题之一。但是,现有的图像分割方法没有统一的标准,传统的图像分割方法只适用于一些特定的场合。因此,研究和开发新的图像分割技术理论和方法显得十分迫切。遗传算法是在生物进化的自然选择和遗传机制中,模拟生物进化过程来计算最优解的一种方法。该算法具有较强的鲁棒性、并行性、自适应性和快速收敛性。它可以应用于图像分割技术来确定分割阈值。因此,本文对基于遗传算法的图像分割进行了研究,并对不同的图像分割算法进行了比较。实验结果表明,基于遗传算法的图像分割效果优于传统的图像分割。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Segmentation Technology Based on Genetic Algorithm
Image segmentation technology is one of the important topics in the field of digital image research. However, there is no uniform standard for existing image segmentation methods, and the traditional image segmentation method is only suitable for some specific occasions. Therefore, it is very urgent to research and develop new theories and methods of image segmentation technology. Genetic algorithm is a method for calculating the optimal solution by simulating the biological evolution process in the natural selection and genetic mechanism of biological evolution. It has strong robustness, parallelism, adaptability and fast convergence. It can be applied in image segmentation technology to determine the segmentation threshold. Therefore, this paper studies the image segmentation based on genetic algorithm, and compares different image segmentation algorithms. The experimental results show that the image segmentation effect based on genetic algorithm is better than the traditional image segmentation.
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